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Deciphering HIPCHAT: A Swift eDiscovery Transformation

chat apps, phone near computer

The Problem

A major multi-national conglomerate was grappling with the challenge of normalizing multiple HipChat collections for their eDiscovery review platform. The inconsistencies in HipChat’s JSON files and the lack of standardization in fields across different instances made it difficult to import the communications and attachments into most eDiscovery review tools.

The Purpose-Built Solution

Recognizing the intricacies of the HipChat data, we developed tailored scripts for the various collections at hand. These scripts were designed to efficiently extract targeted content from the disparate data, ensuring compatibility with the eDiscovery review platform. This meant transforming the unstructured HipChat data into a format where the review team could easily access both communication content and stored documents.

The Product
In under a week, we successfully managed to extract and normalize the necessary content, allowing the review team to view all pertinent information seamlessly. Our innovative approach was lauded by the legal team that hired us, marking the project as a significant technological victory.

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chat apps collections emerging data types forensics hipchat
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